Authentication systems aim to identify fraudulent users even though such users possess credentials to gain access to a legitimate user's account information. For example, each login attempt is received at a service provider at a particular time and in many cases, a fraudulent user will send login attempts at times outside of those expected by a service provider. Existing adaptive authentication techniques compare information associated with a login attempt, such as the time of the login and a location from where the login originated, with a historical record of a typical user who exhibits some expected login behavior. For example, if a high percentage of prior login attempts received by the service provider from a particular user occur between the hours of 6 AM and 11 PM daily and from locations within the continental United States, then login attempts between 2 AM and 4 AM from locations across Eastern Europe, have a high risk of being a fraudulent user.
The need for improved and comprehensive authentication systems is rising every day, for example, due to the increase in cybercrime and fraud. Many adaptive authentication systems employ a number of different authentication methods. Authentication methods include, for example, simple passwords, one-time passcodes, biometrics, tokens and certificates. Existing authentication systems select one or more suitable authentication methods based on usability and cost constraints. A need, though, remains for improved techniques for selecting a suitable authentication method among a plurality of available authentication methods.